code: def kl(self, other=None):
      if self.deterministic:
          return torch.Tensor([0.0])
      else:
          if other is None:
              return 0.5 * torch.sum(
                  torch.pow(self.mean, 2)
                  + self.var
                  - 1.0
                  - self.logvar,
                  dim=[1, 2, 3],
              )
          else:
              return 0.5 * torch.sum(
                  torch.pow(self.mean - other.mean, 2) / other.var
                  + self.var / other.var
                  - 1.0
                  - self.logvar
                  + other.logvar,
                  dim=[1, 2, 3],
              )
  
file_path: generative-models/sgm/modules/distributions/distributions.py
imports: import numpy
  import torch
label_desc: Use image node_id 3 for calling the DiagonalGaussianDistribution obj's underlying member method code with example usage: obj.kl(other) and returns: torch, unknown, unknown